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  • 1
    Publication Date: 2019-07-13
    Description: The Ocean Model Intercomparison Project (OMIP) focuses on the physics and biogeochemistry of the ocean component of Earth system models participating in the sixth phase of the Coupled Model Intercomparison Project (CMIP6). OMIP aims to provide standard protocols and diagnostics for ocean models, while offering a forum to promote their common assessment and improvement. It also offers to compare solutions of the same ocean models when forced with reanalysis data (OMIP simulations) vs. when integrated within fully coupled Earth system models (CMIP6). Here we detail simulation protocols and diagnostics for OMIP's biogeochemical and inert chemical tracers. These passive-tracer simulations will be coupled to ocean circulation models, initialized with observational data or output from a model spin-up, and forced by repeating the 1948-2009 surface fluxes of heat, fresh water, and momentum. These so-called OMIP-BGC simulations include three inert chemical tracers (CFC-11, CFC-12, SF [subscript] 6) and biogeochemical tracers (e.g., dissolved inorganic carbon, carbon isotopes, alkalinity, nutrients, and oxygen). Modelers will use their preferred prognostic BGC model but should follow common guidelines for gas exchange and carbonate chemistry. Simulations include both natural and total carbon tracers. The required forced simulation (omip1) will be initialized with gridded observational climatologies. An optional forced simulation (omip1-spunup) will be initialized instead with BGC fields from a long model spin-up, preferably for 2000 years or more, and forced by repeating the same 62-year meteorological forcing. That optional run will also include abiotic tracers of total dissolved inorganic carbon and radiocarbon, CTabio and 14CTabio, to assess deep-ocean ventilation and distinguish the role of physics vs. biology. These simulations will be forced by observed atmospheric histories of the three inert gases and CO2 as well as carbon isotope ratios of CO2. OMIP-BGC simulation protocols are founded on those from previous phases of the Ocean Carbon-Cycle Model Intercomparison Project. They have been merged and updated to reflect improvements concerning gas exchange, carbonate chemistry, and new data for initial conditions and atmospheric gas histories. Code is provided to facilitate their implementation.
    Keywords: Oceanography; Meteorology and Climatology
    Type: GSFC-E-DAA-TN43737 , Geoscientific Model Development (e-ISSN 1991-9603); 10; 6; 2169–2199
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  • 2
    Publication Date: 2019-07-13
    Description: We analyze daily wintertime cyclone variability in the central and eastern Mediterranean during 1958-2001, and identify four distinct cyclone states, corresponding to the presence or absence of cyclones in each basin. Each cyclone state is associated with wind flows that induce characteristic patterns of cooling via turbulent (sensible and latent) heat fluxes in the eastern Mediterranean basin and Aegean Sea. The relative frequency of occurrence of each state determines the heat loss from the Aegean Sea during that winter, with largest heat losses occurring when there is a storm in the eastern but not central Mediterranean (eNOTc), and the smallest occurring when there is a storm in the central but not eastern Mediterranean (cNOTe). Time series of daily cyclone states for each winter allow us to infer Aegean Sea cooling for winters prior to 1985, the earliest year for which we have daily heat flux observations. We show that cyclone states conducive to Aegean Sea convection occurred in 1991/1992 and 1992/1993, the winters during which deep water formation was observed in the Aegean Sea, and also during the mid-1970s and the winters of 1963/1964 and 1968/1969. We find that the eNOTc cyclone state is anticorrelated with the North Atlantic Oscillation (NAO) prior to 1977/1978. After 1977/1978, the cNOTe state is anticorrelated with both the NAO and the North Caspian Pattern (NCP), showing that the area of influence of large scale atmospheric teleconnections on regional cyclone activity shifted from the eastern to the central Mediterranean during the late 1970s. A trend toward more frequent occurrence of the positive phase of the NAO produced less frequent cNOTe states since the late 1970s, increasing the number of days with strong cooling of the Aegean Sea surface waters.
    Keywords: Earth Resources and Remote Sensing; Meteorology and Climatology
    Type: GSFC-E-DAA-TN11507 , Regional Environmental Change (ISSN 1436-3798); 14; 5; 1713-1723
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  • 3
    Publication Date: 2019-07-13
    Description: The ocean is one of the principal reservoirs of CO2, a greenhouse gas, and therefore plays a crucial role in regulating Earth's climate. Currently, the ocean sequesters about a third of anthropogenic CO2 emissions, mitigating the human impact on climate. At the same time, the deeper ocean represents the largest carbon pool in the Earth System and processes that describe the transfer of carbon from the surface of the ocean to depth are intimately linked to the effectiveness of carbon sequestration.The ocean biological pump (OBP), which involves several biogeochemical processes, is a major pathway for transfer of carbon from the surface mixed layer into the ocean interior. About 75 of the carbon vertical gradient is due to the carbon pump with only 25 attributed to the solubility pump. However, the relative importance and role of the two pumps is poorly constrained. OBP is further divided to the organic carbon pump (soft tissue pump) and the carbonate pump, with the former exporting about 10 times more carbon than the latter through processes like remineralization.Major uncertainties about OBP, and hence in the carbon uptake and sequestration, stem from uncertainties in processes involved in OBP such as particulate organicinorganic carbon sinkingsettling, remineralization, microbial degradation of DOC and uptakegrowth rate changes of the ocean biology. The deep ocean is a major sink of atmospheric CO2 in scales of hundreds to thousands of years, but how the export efficiency (i.e. the fraction of total carbon fixation at the surface that is transported at depth) is affected by climate change remains largely undetermined. These processes affect the ocean chemistry (alkalinity, pH, DIC, particulate and dissolved organic carbon) as well as the ecology (biodiversity, functional groups and their interactions) in the ocean. It is important to have a rigorous, quantitative understanding of the uncertainties involved in the observational measurements, the models and the projections of future changes.
    Keywords: Environment Pollution; Oceanography
    Type: GSFC-E-DAA-TN17734 , IMBER Update, IMBER Newsletter; 24; 10-13
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  • 4
    Publication Date: 2019-07-13
    Description: Planetary carbon cycle involves multiple phenomena, acting at variety of temporal and spacial scales. The typical times range from minutes for leaf stomata physiology to centuries for passive soil carbon pools and deep ocean layers. So, finding a satisfactory equilibrium state becomes a challenging and computationally expensive task. Here we present the spin-up processes for different configurations of the GISS Carbon Cycle model from the model forced with MODIS observed Leaf Area Index (LAI) and prescribed ocean to the prognostic LAI and to the model fully coupled to the dynamic ocean and ocean biology. We investigate the time it takes the model to reach the equilibrium and discuss the ways to speed up this process. NASA Goddard Institute for Space Studies General Circulation Model (GISS ModelE2) is currently equipped with all major algorithms necessary for the simulation of the Global Carbon Cycle. The terrestrial part is presented by Ent Terrestrial Biosphere Model (Ent TBM), which includes leaf biophysics, prognostic phenology and soil biogeochemistry module (based on Carnegie-Ames-Stanford model). The ocean part is based on the NASA Ocean Biogeochemistry Model (NOBM). The transport of atmospheric CO2 is performed by the atmospheric part of ModelE2, which employs quadratic upstream algorithm for this purpose.
    Keywords: Meteorology and Climatology
    Type: GSFC-E-DAA-TN26843 , AGU Fall Meeting; 14-18 Dec. 2015; San Francisco, CA; United States
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  • 5
    Publication Date: 2019-07-13
    Description: Sensitivities of the oceanic biological pump within the GISS (Goddard Institute for Space Studies ) climate modeling system are explored here. Results are presented from twin control simulations of the air-sea CO2 gas exchange using two different ocean models coupled to the same atmosphere. The two ocean models (Russell ocean model and Hybrid Coordinate Ocean Model, HYCOM) use different vertical coordinate systems, and therefore different representations of column physics. Both variants of the GISS climate model are coupled to the same ocean biogeochemistry module (the NASA Ocean Biogeochemistry Model, NOBM), which computes prognostic distributions for biotic and abiotic fields that influence the air-sea flux of CO2 and the deep ocean carbon transport and storage. In particular, the model differences due to remineralization rate changes are compared to differences attributed to physical processes modeled differently in the two ocean models such as ventilation, mixing, eddy stirring and vertical advection. GISSEH(GISSER) is found to underestimate mixed layer depth compared to observations by about 55% (10 %) in the Southern Ocean and overestimate it by about 17% (underestimate by 2%) in the northern high latitudes. Everywhere else in the global ocean, the two models underestimate the surface mixing by about 12-34 %, which prevents deep nutrients from reaching the surface and promoting primary production there. Consequently, carbon export is reduced because of reduced production at the surface. Furthermore, carbon export is particularly sensitive to remineralization rate changes in the frontal regions of the subtropical gyres and at the Equator and this sensitivity in the model is much higher than the sensitivity to physical processes such as vertical mixing, vertical advection and mesoscale eddy transport. At depth, GISSER, which has a significant warm bias, remineralizes nutrients and carbon faster thereby producing more nutrients and carbon at depth, which eventually resurfaces with the global thermohaline circulation especially in the Southern Ocean. Because of the reduced primary production and carbon export in GISSEH compared to GISSER, the biological pump efficiency, i.e., the ratio of primary production and carbon export at 75 m, is half in the GISSEH of that in GISSER, The Southern Ocean emerges as a key region where the CO2 flux is as sensitive to biological parameterizations as it is to physical parameterizations. The fidelity of ocean mixing in the Southern Ocean compared to observations is shown to be a good indicator of the magnitude of the biological pump efficiency regardless of physical model choice.
    Keywords: Meteorology and Climatology
    Type: GSFC-E-DAA-TN20083 , Biogeosciences; 11; 4; 1137-1154
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  • 6
    Publication Date: 2019-07-13
    Description: Results from twin control simulations of the preindustrial CO2 gas exchange (natural flux of CO2) between the ocean and the atmosphere are presented here using the NASA-GISS climate model, in which the same atmospheric component (modelE2) is coupled to two different ocean models, the Russell ocean model and HYCOM. Both incarnations of the GISS climate model are also coupled to the same ocean biogeochemistry module (NOBM) which estimates prognostic distributions for biotic and abiotic fields that influence the air-sea flux of CO2. Model intercomparison is carried out at equilibrium conditions and model differences are contrasted with biases from present day climatologies. Although the models agree on the spatial patterns of the air-sea flux of CO2, they disagree on the strength of the North Atlantic and Southern Ocean sinks mainly because of kinematic (winds) and chemistry (pCO2) differences rather than thermodynamic (SST) ones. Biology/chemistry dissimilarities in the models stem from the different parameterizations of advective and diffusive processes, such as overturning, mixing and horizontal tracer advection and to a lesser degree from parameterizations of biogeochemical processes such as gravitational settling and sinking. The global meridional overturning circulation illustrates much of the different behavior of the biological pump in the two models, together with differences in mixed layer depth which are responsible for different SST, DIC and nutrient distributions in the two models and consequently different atmospheric feedbacks (in the wind, net heat and freshwater fluxes into the ocean).
    Keywords: Meteorology and Climatology
    Type: GSFC-E-DAA-TN20084 , Ocean Modelling; 66; 26-44
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  • 7
    Publication Date: 2019-07-13
    Description: In this paper, we present a database of the basic regimes of the carbon cycle in the ocean, the 'ocean carbon states', as obtained using a data mining/pattern recognition technique in observation-based as well as model data. The goal of this study is to establish a new data analysis methodology, test it and assess its utility in providing more insights into the regional and temporal variability of the marine carbon cycle. This is important as advanced data mining techniques are becoming widely used in climate and Earth sciences and in particular in studies of the global carbon cycle, where the interaction of physical and biogeochemical drivers confounds our ability to accurately describe, understand, and predict CO2 concentrations and their changes in the major planetary carbon reservoirs. In this proof-of-concept study, we focus on using well-understood data that are based on observations, as well as model results from the NASA Goddard Institute for Space Studies (GISS) climate model. Our analysis shows that ocean carbon states are associated with the subtropical-subpolar gyre during the colder months of the year and the tropics during the warmer season in the North Atlantic basin. Conversely, in the Southern Ocean, the ocean carbon states can be associated with the subtropical and Antarctic convergence zones in the warmer season and the coastal Antarctic divergence zone in the colder season. With respect to model evaluation, we find that the GISS model reproduces the cold and warm season regimes more skillfully in the North Atlantic than in the Southern Ocean and matches the observed seasonality better than the spatial distribution of the regimes. Finally, the ocean carbon states provide useful information in the model error attribution. Model air-sea CO2 flux biases in the North Atlantic stem from wind speed and salinity biases in the subpolar region and nutrient and wind speed biases in the subtropics and tropics. Nutrient biases are shown to be most important in the Southern Ocean flux bias.
    Keywords: Meteorology and Climatology; Oceanography
    Type: GSFC-E-DAA-TN54528 , Earth System Science Data (ISSN 1866-3508) (e-ISSN 1866-3516); 10; 1; 609-626
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  • 8
    Publication Date: 2019-07-13
    Description: Modeling is an important tool for understanding AMOC on all timescales. Mechanistic studies of modern AMOC variability have been hampered by a lack of consistency between free-running models and the sensitivity of AMOC to resolution and parameterization. Recent work within the framework of the phase two Coordinated Ocean- Reference Experiments (CORE-II) addresses this issue head on, looking at model differences of AMOC mean state and interannual variability. One consistent feature across the models is that AMOC mean transport is related to mixed layer depths and Labrador Sea salt content, whereas interannual variability is primarily associated with Labrador Sea temperature anomalies. This is consistent with the hypothesized importance of salt balance for AMOC variability on geological timescales. The simulated relationships between AMOC and subsurface temperature anomalies in fully coupled climate models reveal subsurface AMOC fingerprints that could be used to reconstruct historical AMOC variations at low frequency.With the lack of long-term AMOC observations, models of ocean state that assimilate observational data have been explored as a way to reconstruct AMOC, but comparisons between models indicate they are quite variable in their AMOC representations. Karspeck et al. (2015) found that historical reconstructions of AMOC in such models are sensitive to the details of the data assimilation procedure. The ocean data assimilation community continues to address these issues through improved models and methods for estimating and representing error information.Two objectives of paleoclimate modeling are 1) to provide mechanistic information for interpretation of paleoclimate observations, and 2) to test the ability of predictive models to simulate Earth's climate under different background forcing states. In a good example of the first objective, Schmittner and Lund (2015) and Menviel et al. (2014) provided key information about the proxy signals expected under freshwater disturbance of AMOC, which were used to support the paleoclimate observations made by Henry et al. (2016). In an example of the second objective, Muglia and Schmittner (2015) analyzed Third Paleoclimate Modeling Intercomparison Project (PMIP3) models of the Last Glacial Maximum (LGM) and found consistently more intense and deeper AMOC transports relative to preindustrial simulations, counter to the paleoclimate consensus of LGM conditions, indicating that some processes are not well represented in the PMIP3 models. One challenge is to find adequate paleo observations against which to test these models. PMIP is now in phase 4 (part of CMIP6), which includes experiments covering five periods in Earth's history: the last millennium, last glacial maximum, last interglacial, and the mid-Pliocene. Newly compiled paleoclimate datasets from the PAGES2k project, more transient simulations, and participation of isotope enabled models planned for CMIP6PMIP4 will enable richer paleo data-model comparisons in the near future.
    Keywords: Oceanography
    Type: Report 2017-3 , GSFC-E-DAA-TN45417 , US Climate Variability and Predictability (CLIVAR) Workshop; 23-25 May 2016; Boulder, CO; United States
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  • 9
    Publication Date: 2019-07-13
    Description: The Flux-Anomaly-Forced Model Intercomparison Project (FAFMIP) aims to investigate the spread in simulations of sea-level and ocean climate change in response to CO2 forcing by atmosphere-ocean general circulation models (AOGCMs). It is particularly motivated by the uncertainties in projections of ocean heat uptake, global-mean sealevel rise due to thermal expansion and the geographical patterns of sea-level change due to ocean density and circulation change. FAFMIP has three tier-1 experiments, in which prescribed surface flux perturbations of momentum, heat and freshwater respectively are applied to the ocean in separate AOGCM simulations. All other conditions are as in the pre-industrial control. The prescribed fields are typical of pattern and magnitude of changes in these fluxes projected by AOGCMs for doubled CO2 concentration. Five groups have tested the experimental design with existing AOGCMs. Their results show diversity in the pattern and magnitude of changes, with some common qualitative features. Heat and water flux perturbation cause the dipole in sea-level change in the North Atlantic, while momentum and heat flux perturbation cause the gradient across the Antarctic Circumpolar Current. The Atlantic meridional overturning circulation (AMOC) declines in response to the heat flux perturbation, and there is a strong positive feedback on this effect due to the consequent cooling of sea-surface temperature in the North Atlantic, which enhances the local heat input to the ocean. The momentum and water flux perturbations do not substantially affect the AMOC. Heat is taken up largely as a passive tracer in the Southern Ocean, which is the region of greatest heat input, while the weakening of the AMOC causes redistribution of heat towards lower latitudes. Future analysis of these and other phenomena with the wider range of CMIP6 FAFMIP AOGCMs will benefit from new diagnostics of temperature and salinity tendencies, which will enable investigation of the model spread in behaviour in terms of physical processes as formulated in the models.
    Keywords: Meteorology and Climatology
    Type: GSFC-E-DAA-TN37351 , Geoscientific Model Development (e-ISSN 1991-9603); 9; 11; 3993–4017
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  • 10
    Publication Date: 2019-07-13
    Description: During the fifth phase of the Coupled Model Intercomparison Project (CMIP5) substantial efforts were made to systematically assess the skill of Earth system models. One goal was to check how realistically representative marine biogeochemical tracer distributions could be reproduced by models. In routine assessments model historical hindcasts were compared with available modern biogeochemical observations. However, these assessments considered neither how close modeled biogeochemical reservoirs were to equilibrium nor the sensitivity of model performance to initial conditions or to the spin-up protocols. Here, we explore how the large diversity in spin-up protocols used for marine biogeochemistry in CMIP5 Earth system models (ESMs) contributes to model-to-model differences in the simulated fields. We take advantage of a 500-year spin-up simulation of IPSL-CM5A-LR to quantify the influence of the spin-up protocol on model ability to reproduce relevant data fields. Amplification of biases in selected biogeochemical fields (O2, NO3, Alk-DIC) is assessed as a function of spin-up duration. We demonstrate that a relationship between spin-up duration and assessment metrics emerges from our model results and holds when confronted with a larger ensemble of CMIP5 models. This shows that drift has implications for performance assessment in addition to possibly aliasing estimates of climate change impact. Our study suggests that differences in spin-up protocols could explain a substantial part of model disparities, constituting a source of model-to- model uncertainty. This requires more attention in future model intercomparison exercises in order to provide quantitatively more correct ESM results on marine biogeochemistry and carbon cycle feedbacks.
    Keywords: Meteorology and Climatology; Statistics and Probability
    Type: GSFC-E-DAA-TN32395 , Geoscientific Model Development; 9; 5; 1827-1851
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